#  Copyright (c) ZenML GmbH 2022. All Rights Reserved.
#
#  Licensed under the Apache License, Version 2.0 (the "License");
#  you may not use this file except in compliance with the License.
#  You may obtain a copy of the License at:
#
#       https://www.apache.org/licenses/LICENSE-2.0
#
#  Unless required by applicable law or agreed to in writing, software
#  distributed under the License is distributed on an "AS IS" BASIS,
#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express
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from steps.evaluators import evaluator
from steps.importers import importer
from steps.normalizers import normalizer
from steps.trainers import trainer

from zenml import pipeline
from zenml.config import DockerSettings
from zenml.integrations.constants import TENSORFLOW

docker_settings = DockerSettings(required_integrations=[TENSORFLOW])


@pipeline(enable_cache=True, settings={"docker": docker_settings})
def mnist_pipeline(epochs: int = 2, lr: float = 0.001):
    X_train, X_test, y_train, y_test = importer()
    X_trained_normed, X_test_normed = normalizer(
        X_train=X_train, X_test=X_test
    )
    model = trainer(
        X_train=X_trained_normed, y_train=y_train, epochs=epochs, lr=lr
    )
    evaluator(X_test=X_test_normed, y_test=y_test, model=model)
